Scheduling Optimization and Comparative Analysis of Twin 40 Feet Yard Crane Based on SAGA

doi:10.16182/j.issn1004731x.joss.21-0291

Abstract

Abstract:

Based on the operating characteristics of twin 40 ft yard crane, the scheduling models of the single-container yard crane, twin 40 ft yard crane with single-lift structure and twin 40 ft yard crane with twin-lift structure in the mixed container area are established respectively to minimize the operating time. simulate anneal genetic algorithm(SAGA) hybrid algorithm is used in the yard crane scheduling model to optimize the yard crane equipment configuration and scheduling strategy, shorten the average loading and unloading time, and improve the operation efficiency of the automatic terminal. By comparing the operation efficiency of three kinds of cranes under the condition of different adjacent box proportion, total task volume and shell number of mixed stack box area. The results show that the efficiency of twin 40 ft yard crane is higher than that of single-container yard crane, and the effectiveness of the scheduling model and algorithm is verified.

Key words: automatic container terminal, yard mixed container area, twin 40 ft yard crane, single-container yard crane, simulate anneal genetic algorithm(SAGA)

CLC Number:

TP391.9

Meng Yu, Zhenli Xu, Tianjiao Tan. Scheduling Optimization and Comparative Analysis of Twin 40 Feet Yard Crane Based on SAGA[J]. Journal of System Simulation, 2022, 34(8): 1885-1898.

Figures/Tables 22

Fig. 1

Table 1

Fig. 2

Fig. 3

Fig. 4

Fig. 5

Fig. 6

Fig. 7

Fig. 8

Table 2

Fig. 9

Fig. 10

Fig. 11

Fig. 12

Fig. 13

Fig. 14

Table 3

Table 4

Table 5

Fig. 15

Fig. 16

Fig. 17

References 10

1	Virgile Galle, Cynthia Barnhart, Patrick Jaillet. Yard Crane Scheduling for Container Storage, Retrieval, and Relocation[J]. European Journal of Operational Research(S0377-2217), 2018, 271(1): 288-316.
2	Chu Feng, Man Xiaoyi, Zheng Feifeng, et al. Two Yard Crane Scheduling with Dynamic Processing Time and Interference[J]. IEEE Transactions on Intelligent Transportation Systems(S1524-9050), 2018, 19(12): 3775-3784.
3	Lei Dingyou, Zhang Peng, Zhang Yinggui, et al. Research on Optimization of Multi Stage Yard Crane Scheduling Based on Genetic Algorithm[J].Journal of Ambient Intelligence and Humanized Computing(S1868-5137), 2020, 11(2): 483-494. DOI:10.1007/s12652-018-0918-9 .
4	Yu Kai, Yang Jingcheng. MILP Model and a Rolling Horizon Algorithm for Crane Scheduling in a Hybrid Storage Container Terminal[J]. Mathematical Problems in Engineering: Theory, Methods and Applications(S1024-123X), 2019(Pt.1): 4739376. DOI:10.1155/2019/4739376 .
5	叶军, 陈璐. 码头出口箱的场吊作业调度模型及遗传算法研究[J]. 工业工程与管理, 2017, 22(4): 100-106, 114. DOI:10.19495/j.cnki.1007-5429.2017.04.014 .
	Ye Jun, Chen Lu. Mathematical Model and Genetic Algorithm for Multiple Yard Cranes to Load Outbound Containers in a Maritime Terminal[J]. Industrial Engineering and Management, 2017, 22(4): 100-106, 114. DOI:10.19495/j.cnki.1007-5429.2017.04.014 .
6	杨小明, 徐子奇, 张梦天, 等. 穿越式自动化轨道吊任务分配与作业序列联合优化[J]. 计算机集成制造系统, 2020, 26(11): 3094-3107. DOI:10.13196/j.cims.2020.11.020 .
	Yang Xiaoming, Xu Ziqi, Zhang Mengtian, et al. Integrated Optimization for Task Assignment and Sequence Decision of Cross-Over Twin Automated Rail Mounted Gantries[J]. Computer Integrated Manufacturing Systems, 2020, 26(11): 3094-3107. DOI:10.13196/j.cims.2020.11.020 .
7	Xu Weimin, Li Yunlin, Chu Jianxin, et al. Modeling of an Underactuated Nonlinear Double-Container Overhead Crane[J]. Advanced Materials Research(S1662-8985), 2012, 1673(960): 680-687. DOI:10.4028/www.scientific.net/AMR.479-481.680 .
8	徐为民, 徐攀. 不确定扰动下双起升桥吊双吊具鲁棒自适应滑模同步协调控制[J]. 控制与决策, 2016, 31(7): 1192-1198. DOI:10.13195/j.kzyjc.2015.0621 .
	Xu Weimin, Xu Pan. Robust Adaptive Sliding Mode Synchronous Control of Double-Container for Twin-Lift Overhead Cranes with Uncertain Disturbances[J].Control and Decision, 2016, 31(7): 1192-1198. DOI:10.13195/j.kzyjc.2015.0621 .
9	彭勃华, 徐为民, 褚建新, 等. 基于直接自适应的桥吊双吊具同步控制[J]. 控制工程, 2018, 25(5): 930-937. DOI:10.14107/j.cnki.kzgc.161326 .
	Peng Bohua, Xu Weimin, Chu Jianxin, et al. Direct Adaptive Controllers for Position Synchronization of Double-Container Overhead Crane System[J]. Control Engineering of China, 2018, 25(5): 930-937. DOI:10.14107/j.cnki.kzgc.161326 .
10	王志利, 王光辉, 徐诚瑜. 双40英尺集装箱吊具上架系统的对比分析[J]. 港口装卸, 2011(5): 4-7.
	Wang Zhili, Wang Guanghui, Xu Chengyu. Comparative Analysis of Double 40-foot Container Hanger System [J]. Port Handling, 2011(5): 4-7.

集装箱作业特点	任务类型	进/出口箱	集卡类型	集卡停留点	起始位置	目标位置
海侧- 存箱	存箱	进口箱	内集卡	海侧暂存区	海侧暂存区	箱区某位置
陆侧- 存箱	存箱	出口箱	外集卡	陆侧暂存区	陆侧暂存区	箱区某位置
陆侧- 取箱	取箱	进口箱	外集卡	陆侧暂存区	箱区某位置	陆侧暂存区
海侧- 取箱	取箱	出口箱	内集卡	海侧暂存区	箱区某位置	海侧暂存区

任务编号	任务类别	集卡类别	集卡停靠位置	贝位	栈	层	任务存储位置
1	0	1	(0, 5, 1)	25	5	3	(25, 5, 3)
2	1	1	(0, 1, 1)	27	1	1	(27, 1, 1)
3	0	0	(31, 6, 1)	6	6	2	(6, 2, 2)
4	0	1	(0, 5, 1)	15	5	2	(15, 5, 2)
5	1	1	(0, 2, 1)	11	2	4	(11, 2, 4)
6	0	0	(31, 5, 1)	6	5	2	(6, 5, 2)
7	1	1	(0, 4, 1)	11	4	1	(11, 4, 1)
8	1	0	(31, 4, 1)	26	4	2	(26, 4, 2)
9	0	0	(31, 1, 1)	26	1	2	(26, 1, 2)
10	0	0	(31, 2, 1)	21	2	4	(21, 2, 4)

相邻箱占比/%	单吊具场桥场桥任务完成时间/min	单起升双40 ft场桥场桥任务完成时间/min	双起升双40 ft场桥场桥任务完成时间/min
0	108.79	106.86	90.50
25	112.05	101.17	85.78
50	107.43	80.03	82.40
75	105.28	68.93	83.18
100	102.59	56.56	82.13

作业任务量	单吊具场桥场桥任务完成时间/min	单起升双40 ft场桥场桥任务完成时间/min	双起升双40 ft场桥场桥任务完成时间/min
20	50.09	34.36	37.45
40	107.43	80.03	82.40
60	165.85	126.37	131.65
80	226.15	174.33	179.12
100	281.48	213.82	215.27

贝位数量	单吊具场桥场桥任务完成时间/min	单起升双40 ft场桥场桥任务完成时间/min	双起升双40 ft场桥场桥任务完成时间/min
20	106.39	78.03	77.63
30	107.43	80.03	82.40
40	105.59	80.32	81.87
50	121.71	104.66	103.42
60	138.06	116.24	114.08